Attributions of social interactions: Driving among self-driving vs. conventional vehicles

Mixed traffic-roadway shared by automated (AV) and conventional vehicles-is anticipated to take place in the next few decades as the production and acceptance of automated vehicles increases. However, interactions between AVs and drivers in conventional vehicles are projected to be problematic. The current study aimed to examine the relationship among intentionality attributions, emotional reactions, and intended driver behaviors in response to hypothetical traffic scenarios when the actions were performed by human-drivers vs. self-driving cars. Three studies were conducted: Pilot Study 1: modifications of the Propensity for Angry Driving Scale (PADS), Pilot Study 2: verification of the instructions of the modified PADS using a college student sample, and Main Study: collection of ratings of intentionality, emotions, intended responses, trait aggression, and demographics upon reading human-driver and self-driving car PADS using a heterogeneous online sample. Intended responses were more severe in the self-driving car conditions, even though the self-driving car's actions were attributed as less intentional. Self-driving cars portrayed as having a heart and a mind led to similar behavioral responses but different affective ratings. Individuals who attributed the actions intentionally and rated their emotions more negatively had more aggressive intended responses. The results suggest that people perceive and interpret the capacities and responsibilities of the actors-human-driver and self-driving car-differently due to differential mind attributions. As technology in transportation matures, examining people's behaviors and intentions in mixed traffic can lead to better preparation for the future roads and maximize the safety benefits of automated vehicles.